An Extended Catalog of Galaxy-Galaxy Strong Gravitational Lenses Discovered in DES Using Convolutional Neural Networks

Jacobs, C.; Collett, T.; Glazebrook, K.; Buckley-Geer, E.; Diehl, H. T.; Lin, H.; McCarthy, C.; Qin, A. K.; Odden, C.; Escudero, M. Caso; Dial, P.; Yung, V. J.; Gaitsch, S.; Pellico, A.; Lindgren, K. A.; Abbott, T. M. C.; Annis, J.; Avila, S.; Brooks, D.; Burke, D. L.; Carnero Rosell, A.; Kind, M. Carrasco; Carretero, J.; da Costa, L. N.; De Vicente, J.; Fosalba, P.; Frieman, J.; Garcia-Bellido, J.; Gaztanaga, E.; Goldstein, D. A.; Grün, D.; Gründl, R. A.; Gschwend, J.; Hollowood, D. L.; Honscheid, K.; Hoyle, B.; James, D. J.; Krause, E.; Kuropatkin, N.; Lahav, O.; Lima, M.; Maia, M. A. G.; Marshall, J. L.; Miquel, R.; Plazas, A. A.; Roodman, A.; Sanchez, E.; Scarpine, V.; Serrano, S.; Sevilla-Noarbe, I.; Smith, M.; Sobreira, F.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Vikram, V.; Walker, A. R. und Zhang, Y. (2019): An Extended Catalog of Galaxy-Galaxy Strong Gravitational Lenses Discovered in DES Using Convolutional Neural Networks. In: Astrophysical Journal Supplement Series, Bd. 243, Nr. 1, 17

Abstract

We search Dark Energy Survey (DES) Year 3 imaging for galaxy-galaxy strong gravitational lenses using convolutional neural networks, extending previous work with new training sets and covering a wider range of redshifts and colors. We train two neural networks using images of simulated lenses, then use them to score postage-stamp images of 7.9 million sources from DES chosen to have plausible lens colors based on simulations. We examine 1175 of the highest-scored candidates and identify 152 probable or definite lenses. Examining an additional 20,000 images with lower scores, we identify a further 247 probable or definite candidates. After including 86 candidates discovered in earlier searches using neural networks and 26 candidates discovered through visual inspection of blue-near-red objects in the DES catalog, we present a catalog of 511 lens candidates.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Physik
• Themengebiete: 500 Naturwissenschaften und Mathematik > 530 Physik
• ISSN: 0067-0049
• Sprache: Englisch